Microwaves have a certain penetration during propagation. Through microwave imaging technology, it can obtain the image of the object under the clothes of the scanned (human) body, and then automatically complete the detection of the dangerous objects such as metal instruments, ceramic knives, unknown liquids, and powders which are under the clothes of the scanned body based on the image of the object. During the inspection process, if the detection of suspicious dangerous objects is performed by the directly visual observation of security operators, it will have huge consumption in manpower, financial resources and time. Therefore, it is of great significance to design an automatic detection method to perform the automatic detection of concealed dangerous objects with different attributes and types which are possible to appear on a body shown in a microwave image.
The existing automatic object detection methods are generally divided into two types: the first one is for visible light image data; the second one is for microwave image data, while it is generally for single image detection. The above-mentioned two methods are not applicable to the security inspection system of microwave images for the main reasons are as follows: 1) the imaging mechanism of microwave images and visible light images are essentially different, and the dangerous objects detection method applied to visible light images cannot be directly applied to microwave images since the microwave image has low grayscale, low resolution, and is affected by speckle multiplicative noise; 2) since dangerous objects will show certain similarities and differences in adjacent images due to the difference in sampling angles, and it will depend on imaging quality too much and is easy to cause false detection when the detection is only performed on a single image, hence the feature detection method based on a single image cannot meet the requirement of the accuracy of the automatic detection of dangerous objects in a microwave security inspection system.